Grantee Research Project Results
2023 Progress Report: Assessment of neurotoxicity of mixtures of PFAS and other neuroactive organic pollutants through integrated in silico, in vitro cellular and in vivo models
EPA Grant Number: R840451Title: Assessment of neurotoxicity of mixtures of PFAS and other neuroactive organic pollutants through integrated in silico, in vitro cellular and in vivo models
Investigators: Aga, Diana S. , Atilla-Gokcumen, Ekin , Rajan, Krishna , Sirotkin, Howard
Institution: The State University of New York at Buffalo , The State University of New York at Stony Brook
EPA Project Officer: Aja, Hayley
Project Period: October 1, 2022 through September 30, 2025
Project Period Covered by this Report: October 1, 2022 through September 30,2023
Project Amount: $750,000
RFA: Development of Innovative Approaches to Assess the Toxicity of Chemical Mixtures Request for Applications (RFA) (2022) RFA Text | Recipients Lists
Research Category: Safer Chemicals , Children's Health , Health Effects , Computational Toxicology , Human Health , PFAS Treatment , Chemical Safety for Sustainability , New Approach Methods (NAMs) , Mixtures , Non-Vertebrate Animal Testing , CSS
Objective:
This study will integrate in vitro and in silico high throughput testing (HTT) with in vivo tests using zebrafish model to evaluate the neurotoxicity of mixtures of per- and polyfluoroalkyl substances (PFAS), and their mixtures with other organic contaminants. The role of cellular transporters will be evaluated to study the active transport and bioactivity of PFAS and their mixtures. These approaches will assess the role of PFAS in the etiology of neurodevelopmental disorders, particularly in the development of autism spectrum disorder (ASD). The objectives of the study are to: (1) derive information on the effects of PFAS and their mixtures on cellular key events leading to neurotoxicity; (2) develop machine learning toxicity prediction tools to map the multivariate data on the structure and/or functionality of PFAS and other organic contaminants, (3) investigate the role of cellular transporters in PFAS uptake and localization, and (4) validate results from in vitro and in silico approaches using zebrafish model to assess impacts of PFAS on neurodevelopment, and on the development of complex behaviors.
Progress Summary:
Task 1: Twelve PFAS were tested alone, and in mixtures, as they occurred in the environment and in human blood. Task 1.1 Testing of individual PFAS to establish concentration-effect relationships was completed for 12 PFAS. Initial experiments and method development were performed for task 1.2. The in vitro bioassay endpoints were neurotoxicity and mitochondrial toxicity (MitoOxTox) as well as oxidative stress response using two cell lines, the differentiated neuroblastoma cell line SH-SY5Y and AREc32. In the mixture composed according to mean concentrations1 all PFAS acted in a “concentration additive” manner. The contribution of each component to the mixture effect varied depending on the toxicity endpoint and was different from the mixture composition. These preliminary results will be further explored.
Task 2: In order to predict the toxicity of PFAS, we need a way to predict properties of these molecules. These properties can then be used in predictive modeling to determine the toxicity of novel PFAS. We have predicted acid dissociation constants (pKa), octanol-water partition coefficients (KOW), and DPMC lipid membrane-water partition coefficients (Klipid-w) of 150 different 8-carbon containing poly-/per-fluoroalkyl carboxylic acids (C8-PFCAs) utilizing COSMO-RS theory for Task 2. Different trends associated with functionalization, degree of fluorination, degree of saturation, degree of chlorination, and branching are discussed based upon the predicted values for the partition coefficients. In general, functionalization closest to the carboxylic head group had the greatest impact on the value of the predicted physicochemical properties. We also determined how well our method for calculating properties did compared to experimental and other computational methods. From these results we see that our calculated values are in line with previously calculated values and experimentally measured values. We used mean square error (MAE) and root mean square error (RMSE) to show this. These results also show that our method works for molecules that vary in size.
Task 3: To investigate the specificity between PFAS-CD36 interactions, we carried out mutagenesis studies to disturb the fatty acid binding pocket of CD36 and assess the impact of this disruption on PFAS uptake. The crystal structure of a CD36-fatty acid complex has highlighted a key residue in the active site, K164, that recognized the negatively charged fatty acid head group.1 We generated two mutant forms of CD36 using FusionRed-CD36 construct2, CD36K164Q and CD36K164E, which have impaired fatty acid recognition due to the loss of K164. The transfection efficiencies of all the constructs were comparable to each other as determined by immunofluorescence imaging and were ~65%. WT, CD36K164Q and CDK164E-expressing cells were treated with various PFAS at 10 μM for 4 hours, cells were collected and PFAS content was analyzed using isotopically-labelled PFAS standards and LC QToF-MS. Our results show that the cellular uptake of PFAS increases for WT and mutant forms with increasing carbon chain length consistent with our previous work. We note high variability along biological replicates for WT CD36 expressing cells, we detected a statistically significant decrease (p £ 0.05, t-test) for the uptake of PFOA, PFHxS, and 4:2 FTS in mutant CD36 expressing cells as compared to WT CD36 expressing cells. The uptake of PFDA, PFOS, PFDS, 6:2 FTS and 8:2 FTS remained similar (p > 0.05) between WT and mutant CD36 expressing cells. We are currently running additional experiments with additional biological replicates and to test different exposure conditions.
Task 4: We used zebrafish larvae to assess the effects of PFOS on two fundamental complex behaviors: prey capture and learning. Zebrafish exposed to varying PFOS concentrations (2-20 μM) for differing 48- hour periods were viable through early larval stages. We first assessed the impacts of increasing organismal PFOS bioaccumulation on prey capture and learning, and second, we probed stage-specific sensitivity to PFOS by exposing zebrafish at different developmental stages (0-2 vs 3-5 days post fertilization). Following both assays we measured the amount of PFOS present in each larva. PFOS levels varied in larvae from different groups within each experimental paradigm. Significant negative correlations were observed between larval PFOS accumulation and percentage of captured prey, while non-significant negative correlations were observed between PFOS accumulation and experienced-induced prey capture learning. These findings suggest that PFOS accumulation negatively affects larval zebrafish’s ability to perform complicated multisensory behaviors and highlight potential risks of PFOS exposure to animals in the wild, with implications to human health.
Future Activities:
Task 1: The mixture experiments using 12 PFAS, with designed mixtures as they occur in the environment and human blood, will be completed in early 2024; a paper will be drafted upon completion of these experiments. We could confirm “concentration addition” as model for most PFAS mixtures, unless the individual components were below visible effects but still somewhat contributed to the mixture. We will further explore this PFAS behavior to better understand the mixture effects. We will test the hypothesis that PFAS mixtures, and PFAS mixed with other chemicals in complex environmental samples produce a “something from nothing effect”, i.e., that even if the mixture components are present in concentrations below which there is no effect observable, the mixture will have a measurable effect, which can be describe by the mixture model of “concentration addition”. To this end, we will prepare mixtures with larger number of components, using the same tests strategy that was developed for the 12 component mixtures. Subsequently, we will test binary mixtures of PFAS and other microcontaminants in Task 1.3.
Task 2: Previously, there was work done on using generated chemical descriptors to be used in grouping PFAS via unsupervised machine learning. We will advance these techniques by further investigation of 3 previous data and newly calculated chemical properties. We will also investigate methods to calculate physicochemical properties of PFAS by coupling first principle calculations with machine learning methods. We propose to explore classification schemes to unravel complex correlations between physicochemical properties and molecular structure that may provide insight into relative toxicity of different species of PFAS. We will use these data to link to in vitro and in vivo experiments being performed in the other Research Tasks.
Task 3: We will continue our investigations on the interactions between CD36 and PFAS. Specifically, we will carry out different exposure conditions in cells expressing WT and mutant forms of CD36 and include fatty acid competition experiments with PFAS. These results will further support our hypothesis that PFAS interact with CD36 via its fatty acid binding pocket. We will also expand these studies to different fatty acid transport proteins (FATP1-6) and test the effect of increasing their levels on the uptake of PFAS. These results will help us to determine the role of these transporters on the uptake of PFAS and their different mixtures and assess the mechanisms of PFAS accumulation in cells.
Task 4: We will continue to test the effects of additional PFAS compounds on zebrafish survival, locomotion, prey capture and social behavior. These assays involve exposing early-stage larva to PFAS and monitoring the behavioral impacts at 6- or 7-days post fertilization (locomutation and prey capture) and 3 weeks post fertilization (social behavior). The zebrafish behavioral monitoring systems used include the Zebrabox (Viewpont) and the Zantiks system (Zantiks).
References:
Pepino MY, Kuda O, Samovski D, Abumrad NA. Structure-function of CD36 and importance of fatty acid signal transduction in fat metabolism. Annu Rev Nutr. 2014;34:281-303.
Camdzic M, Aga DS, Atilla-Gokcumen GE. Cellular Interactions and Fatty Acid Transporter CD36- Mediated Uptake of Per- and Polyfluorinated Alkyl Substances (PFAS). Chem Res Toxicol. 2022 Apr 18;35(4):694-702.
Journal Articles on this Report : 2 Displayed | Download in RIS Format
Other project views: | All 2 publications | 2 publications in selected types | All 2 journal articles |
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Su A, Cheng Y, Zhang C, Yang Y, She Y, Rajan K. An artificial intelligence platform for automated PFAS subgroup classification: A discovery tool for PFAS screening. SCIENCE OF THE TOTAL ENVIRONMENT 2024;921(141229) |
R840451 (2023) |
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Zoodsma J, Boonkanon C, Running L, Basharat R, Atilla-Gokcumen G, Aga D, Sirotkin H. Perfluorooctane Sulfonate (PFOS) Negatively Impacts Prey Capture Capabilities in Larval Zebrafish. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2024;. |
R840451 (2023) |
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Supplemental Keywords:
antidepressants, LC/MS/MS, binary mixtures, CD36 transporterThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.